class_docstr: Generic moment.
  
  Our implementations of the reductions approach to fairness
  :footcite:p:`agarwal2018reductions` make use
  of :class:`Moment` objects to describe both the optimization objective
  and the fairness constraints
  imposed on the solution. This is an abstract class for all such objects.
  
  Read more in the :ref:`User Guide <reductions>`.
class_docstr_tok: ["Generic","moment",".","Our","implementations","of","the","reductions","approach","to","fairness",":","footcite",":","p",":","`","agarwal2018reductions","`","make","use","of",":","class",":","`","Moment","`","objects","to","describe","both","the","optimization","objective","and","the","fairness","constraints","imposed","on","the","solution",".","This","is","an","abstract","class","for","all","such","objects",".","Read","more","in","the",":","ref",":","`","User","Guide","<","reductions",">","`","."]
docstr: Calculate the degree to which constraints are currently violated by the predictor.
docstr_tok: ["Calculate","the","degree","to","which","constraints","are","currently","violated","by","the","predictor","."]
code: def gamma(self, predictor):  # noqa: D102
      """Calculate the degree to which constraints are currently violated by the predictor."""
      raise NotImplementedError()
  
file_path: fairlearn/fairlearn/reductions/_moments/moment.py
imports: import pandas
label_desc: Use image node_id 5 for calling the Moment obj's underlying member method code with example usage: obj.gamma(predictor) without return types